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// Targeted by JavaCPP version 1.5.7: DO NOT EDIT THIS FILE

package org.bytedeco.tensorflowlite;

import java.nio.*;
import org.bytedeco.javacpp.*;
import org.bytedeco.javacpp.annotation.*;

import static org.bytedeco.tensorflowlite.global.tensorflowlite.*;
              // Class for friend declarations.

/** WARNING: Experimental interface, subject to change
 * 
 *  SignatureRunner class for running TFLite models using SignatureDef.
 * 
 *  Usage:
 * 
 *  
 *  // Create model from file. Note that the model instance must outlive the
 *  // interpreter instance.
 *  auto model = tflite::FlatBufferModel::BuildFromFile(...);
 *  if (model == nullptr) {
 *    // Return error.
 *  }
 * 
 *  // Create an Interpreter with an InterpreterBuilder.
 *  std::unique_ptr interpreter;
 *  tflite::ops::builtin::BuiltinOpResolver resolver;
 *  if (InterpreterBuilder(*model, resolver)(&interpreter) != kTfLiteOk) {
 *    // Return failure.
 *  }
 * 
 *  // Get the list of signatures and check it.
 *  auto signature_defs = interpreter->signature_def_names();
 *  if (signature_defs.empty()) {
 *    // Return error.
 *  }
 * 
 *  // Get pointer to the SignatureRunner instance corresponding to a signature.
 *  // Note that the pointed SignatureRunner instance has lifetime same as the
 *  // Interpreter instance.
 *  tflite::SignatureRunner* runner =
 *                 interpreter->GetSignatureRunner(signature_defs[0]->c_str());
 *  if (runner == nullptr) {
 *    // Return error.
 *  }
 *  if (runner->AllocateTensors() != kTfLiteOk) {
 *    // Return failure.
 *  }
 * 
 *  // Set input data. In this example, the input tensor has float type.
 *  float* input = runner->input_tensor(0)->data.f;
 *  for (int i = 0; i < input_size; i++) {
 *    input[i] = ...; */
//  }
/** runner->Invoke();
/** 
/**
/** WARNING: This class is *not* thread-safe. The client is responsible for
/** ensuring serialized interaction to avoid data races and undefined behavior.
/**
/** SignatureRunner and Interpreter share the same underlying data. Calling
/** methods on an Interpreter object will affect the state in corresponding
/** SignatureRunner objects. Therefore, it is recommended not to call other
/** Interpreter methods after calling GetSignatureRunner to create
/** SignatureRunner instances. */
@Namespace("tflite") @NoOffset @Properties(inherit = org.bytedeco.tensorflowlite.presets.tensorflowlite.class)
public class SignatureRunner extends Pointer {
    static { Loader.load(); }
    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
    public SignatureRunner(Pointer p) { super(p); }

  /** Returns the key for the corresponding signature. */
  public native @StdString String signature_key();

  /** Returns the number of inputs. */
  public native @Cast("size_t") long input_size();

  /** Returns the number of outputs. */
  public native @Cast("size_t") long output_size();

  /** Read-only access to list of signature input names. */
  public native @Cast("const char**") @StdVector PointerPointer input_names();

  /** Read-only access to list of signature output names. */
  public native @Cast("const char**") @StdVector PointerPointer output_names();

  /** Returns the input tensor identified by 'input_name' in the
   *  given signature. Returns nullptr if the given name is not valid. */
  public native TfLiteTensor input_tensor(@Cast("const char*") BytePointer input_name);
  public native TfLiteTensor input_tensor(String input_name);

  /** Returns the output tensor identified by 'output_name' in the
   *  given signature. Returns nullptr if the given name is not valid. */
  public native @Const TfLiteTensor output_tensor(@Cast("const char*") BytePointer output_name);
  public native @Const TfLiteTensor output_tensor(String output_name);

  /** Change a dimensionality of a given tensor. Note, this is only acceptable
   *  for tensors that are inputs.
   *  Returns status of failure or success. Note that this doesn't actually
   *  resize any existing buffers. A call to AllocateTensors() is required to
   *  change the tensor input buffer. */
  public native @Cast("TfLiteStatus") int ResizeInputTensor(@Cast("const char*") BytePointer input_name,
                                   @StdVector IntPointer new_size);
  public native @Cast("TfLiteStatus") int ResizeInputTensor(String input_name,
                                   @StdVector IntBuffer new_size);
  public native @Cast("TfLiteStatus") int ResizeInputTensor(@Cast("const char*") BytePointer input_name,
                                   @StdVector int[] new_size);
  public native @Cast("TfLiteStatus") int ResizeInputTensor(String input_name,
                                   @StdVector IntPointer new_size);
  public native @Cast("TfLiteStatus") int ResizeInputTensor(@Cast("const char*") BytePointer input_name,
                                   @StdVector IntBuffer new_size);
  public native @Cast("TfLiteStatus") int ResizeInputTensor(String input_name,
                                   @StdVector int[] new_size);

  /** Updates allocations for all tensors, related to the given signature. */
  public native @Cast("TfLiteStatus") int AllocateTensors();

  /** Invokes the signature runner (run the graph identified by the given
   *  signature in dependency order). */
  public native @Cast("TfLiteStatus") int Invoke();
}